A Novel Hybrid Student Model for Personalized Education - Advances in Personalized Web-Based Education - page 90

According to the learner's knowledge level and errors, the system attached her/him
to the appropriate stereotype category, which concerns the student's knowledge level.
The transition of a learner from one stereotype category of knowledge level to another
depicts the state of the learner. In other words, the transition of a learner from one
stereotype category of knowledge level to another reveals if s/he has learned or not
a domain concept, if s/he has forgot a concept or if s/he has assimilated it. In addi-
tion, the presented model includes two more stereotype categories. The one category
concerns the type of errors and helps the system to reason the poor performance of
the learner. The other stereotype category concerns the student's prior knowledge on
other related knowledge domains and helps the system either to identify the learner's
knowledge level or to infer if the student's errors are caused by confusion with her/his
prior knowledge.
The presented novel student model approach has been fully implemented in a
web-based educational application, which teaches the programming language 'C'.
The presented system provides adaptation of the instructional material, taking into
account the individuality of learners in terms of background, skills and pace of
learning. The particular student model includes a fuzzy-weighted qualitative over-
lay model; a rule-based fuzzy system; and a three-dimensional stereotype model.
The first dimension of the three-dimensional stereotype model consists of eight
stereotypes that represent the learner's knowledge level; the second dimension
consists of two stereotypes that concern the type of programming errors (logical
or syntactic) and the third dimension concerns prior knowledge of the student on
other programming languages.
The particular student model allows each learner to complete the e-learning
course at their own pace, taking decisions about which concepts should be
delivered, which concepts need revision and which concepts are known and
do not need rereading. In this way, the system helps learners to save time and
effort during the learning process. The system identifies the alterations on the
state of students' knowledge level, recognizes the misconceptions and needs of a
learner, and reasons them. It tracks the cognitive state transitions of learners by
constructing automatically state-chart diagrams. Thereby, the system recognizes if
a student learns or not, if s/he reads or not, if s/he has difficulty in understanding,
if s/he forgets, if s/he has confused with other programming languages that s/he
has previously learned.